Machine Learning

Intelligent House Price Prediction Using Machine Learning

The Intelligent House Price Prediction Using Machine Learning system is a comprehensive machine learning solution that predicts house prices using various property features including overall quality, living area size, year built, and neighborhood characteristics. This project is ideal for B.Tech, MCA, CSE, and engineering students as their final year project. It uses advanced ensemble algorithms like XGBoost and Gradient Boosting to achieve 93.2% R² accuracy.

The system leverages comprehensive feature engineering and data preprocessing to handle missing values, encode categorical variables, and scale numerical features. It provides interactive visualizations, feature importance analysis, model comparison, and real-time price predictions to help homebuyers, sellers, investors, and real estate professionals make informed decisions.

• Real Estate Price Prediction
• XGBoost (93.2% R² Score)
• Gradient Boosting (91.5% R²)
• Feature Importance Analysis
• Comprehensive Data Preprocessing
• Real-time Price Prediction
• Model Performance Comparison
• Interactive Visualizations
• 5-Fold Cross-Validation
• Flask Web Application